#PACOTES

#install.packages("psych")
#install.packages("chisq.posthoc.test")
#install.packages("summarytools")

library(psych)
## Warning: package 'psych' was built under R version 4.0.5
library(chisq.posthoc.test)

Dados

#dados_videos <- read.csv("dados_aline.csv")
dados_videos <- read.csv("banco_aline_quanti_99.csv")

Análise Descritiva - Geral

describe(dados_videos)
summary(dados_videos)
##  Carimbo.de.data.hora      ID                  q1             q2       
##  Length:99            Length:99          Min.   :2.00   Min.   :1.000  
##  Class :character     Class :character   1st Qu.:3.00   1st Qu.:2.000  
##  Mode  :character     Mode  :character   Median :4.00   Median :2.000  
##                                          Mean   :3.96   Mean   :2.232  
##                                          3rd Qu.:5.00   3rd Qu.:3.000  
##                                          Max.   :6.00   Max.   :4.000  
##        q3              q4               q5               q6         
##  Min.   :1.000   Min.   :  1456   Min.   :  35.0   Min.   :    0.0  
##  1st Qu.:2.000   1st Qu.:  2164   1st Qu.: 285.0   1st Qu.:   54.5  
##  Median :2.000   Median :  5326   Median : 487.0   Median :  156.0  
##  Mean   :2.242   Mean   : 22432   Mean   : 736.3   Mean   : 1100.0  
##  3rd Qu.:3.000   3rd Qu.: 13791   3rd Qu.: 797.0   3rd Qu.:  578.5  
##  Max.   :3.000   Max.   :613011   Max.   :3717.0   Max.   :22000.0  
##        q7                q9             q10             q11       
##  Min.   :   0.00   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:   1.00   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000  
##  Median :   4.00   Median :1.000   Median :2.000   Median :2.000  
##  Mean   :  27.41   Mean   :1.071   Mean   :1.586   Mean   :1.566  
##  3rd Qu.:  11.00   3rd Qu.:1.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :1400.00   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q12             q13             q14             q15       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000  
##  Median :2.000   Median :1.000   Median :2.000   Median :1.000  
##  Mean   :1.717   Mean   :1.495   Mean   :1.556   Mean   :1.273  
##  3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q16             q17             q18             q19       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000  
##  Median :1.000   Median :1.000   Median :2.000   Median :1.000  
##  Mean   :1.444   Mean   :1.101   Mean   :1.667   Mean   :1.424  
##  3rd Qu.:2.000   3rd Qu.:1.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q20             q21             q22             q23       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000  
##  Median :2.000   Median :2.000   Median :2.000   Median :2.000  
##  Mean   :1.737   Mean   :1.636   Mean   :1.616   Mean   :1.586  
##  3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q24             q25             q26             q27       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:2.000  
##  Median :2.000   Median :1.000   Median :2.000   Median :2.000  
##  Mean   :1.566   Mean   :1.333   Mean   :1.717   Mean   :1.899  
##  3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q28             q29             q30             q31       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:1.000   1st Qu.:1.500   1st Qu.:2.000   1st Qu.:2.000  
##  Median :2.000   Median :2.000   Median :2.000   Median :2.000  
##  Mean   :1.687   Mean   :1.747   Mean   :1.838   Mean   :1.859  
##  3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q32             q33             q34             q35       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000  
##  Median :2.000   Median :1.000   Median :2.000   Median :2.000  
##  Mean   :1.667   Mean   :1.434   Mean   :1.545   Mean   :1.657  
##  3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q36             q37             q38             q39       
##  Min.   :1.000   Min.   :1.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.:2.000   1st Qu.:1.000   1st Qu.:1.000   1st Qu.:2.000  
##  Median :2.000   Median :1.000   Median :2.000   Median :2.000  
##  Mean   :1.808   Mean   :1.384   Mean   :1.646   Mean   :1.919  
##  3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000   Max.   :2.000   Max.   :2.000  
##       q40             q41       
##  Min.   :1.000   Min.   :1.000  
##  1st Qu.:2.000   1st Qu.:1.000  
##  Median :2.000   Median :2.000  
##  Mean   :1.939   Mean   :1.626  
##  3rd Qu.:2.000   3rd Qu.:2.000  
##  Max.   :2.000   Max.   :2.000

Provisão de Conteúdo

table<-with(dados_videos,table(q9,q3))
table
##    q3
## q9   1  2  3
##   1 17 34 41
##   2  3  1  3
prop.table(table)
##    q3
## q9           1          2          3
##   1 0.17171717 0.34343434 0.41414141
##   2 0.03030303 0.01010101 0.03030303
chisq.test(dados_videos$q9, dados_videos$q3)
## Warning in chisq.test(dados_videos$q9, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q9 and dados_videos$q3
## X-squared = 2.8637, df = 2, p-value = 0.2389
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
sig<-.05
sigAdj<-sig/(nrow(table)*ncol(table))
sigAdj
## [1] 0.008333333
qnorm(sigAdj/2)
## [1] -2.638257

Informações a respeito de experiência pessoal

table<-with(dados_videos,table(q10,q3))
table
##    q3
## q10  1  2  3
##   1 18  5 18
##   2  2 30 26
prop.table(table)
##    q3
## q10          1          2          3
##   1 0.18181818 0.05050505 0.18181818
##   2 0.02020202 0.30303030 0.26262626
chisq.test(dados_videos$q10, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q10 and dados_videos$q3
## X-squared = 30.079, df = 2, p-value = 2.94e-07
chisq.posthoc.test(table)

Menciona quem são acometidos pela DC

table<-with(dados_videos,table(q11,q3))
table
##    q3
## q11  1  2  3
##   1  3 11 29
##   2 17 24 15
prop.table(table)
##    q3
## q11          1          2          3
##   1 0.03030303 0.11111111 0.29292929
##   2 0.17171717 0.24242424 0.15151515
chisq.test(dados_videos$q11, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q11 and dados_videos$q3
## X-squared = 17.681, df = 2, p-value = 0.0001448
chisq.posthoc.test(table)

Menciona quem está em risco

table<-with(dados_videos,table(q12,q3))
table
##    q3
## q12  1  2  3
##   1  3 10 15
##   2 17 25 29
prop.table(table)
##    q3
## q12          1          2          3
##   1 0.03030303 0.10101010 0.15151515
##   2 0.17171717 0.25252525 0.29292929
chisq.test(dados_videos$q12, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q12 and dados_videos$q3
## X-squared = 2.4729, df = 2, p-value = 0.2904
chisq.posthoc.test(table)

Menciona a DC como uma doença autoimune

table<-with(dados_videos,table(q13,q3))
table
##    q3
## q13  1  2  3
##   1 10 16 24
##   2 10 19 20
prop.table(table)
##    q3
## q13         1         2         3
##   1 0.1010101 0.1616162 0.2424242
##   2 0.1010101 0.1919192 0.2020202
chisq.test(dados_videos$q13, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q13 and dados_videos$q3
## X-squared = 0.61074, df = 2, p-value = 0.7369
chisq.posthoc.test(table)

Menciona que a DC é uma doença hereditária

table<-with(dados_videos,table(q14,q3))
table
##    q3
## q14  1  2  3
##   1  8 11 25
##   2 12 24 19
prop.table(table)
##    q3
## q14          1          2          3
##   1 0.08080808 0.11111111 0.25252525
##   2 0.12121212 0.24242424 0.19191919
chisq.test(dados_videos$q14, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q14 and dados_videos$q3
## X-squared = 5.2898, df = 2, p-value = 0.07101
chisq.posthoc.test(table)

Menciona como a DC afeta o corpo

table<-with(dados_videos,table(q15,q3))
table
##    q3
## q15  1  2  3
##   1 13 24 35
##   2  7 11  9
prop.table(table)
##    q3
## q15          1          2          3
##   1 0.13131313 0.24242424 0.35353535
##   2 0.07070707 0.11111111 0.09090909
chisq.test(dados_videos$q15, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q15 and dados_videos$q3
## X-squared = 1.9381, df = 2, p-value = 0.3794
chisq.posthoc.test(table)

Menciona danos de “vilosidades” no intestino delgado

table<-with(dados_videos,table(q16,q3))
table
##    q3
## q16  1  2  3
##   1  5 21 29
##   2 15 14 15
prop.table(table)
##    q3
## q16          1          2          3
##   1 0.05050505 0.21212121 0.29292929
##   2 0.15151515 0.14141414 0.15151515
chisq.test(dados_videos$q16, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q16 and dados_videos$q3
## X-squared = 9.7527, df = 2, p-value = 0.007625
chisq.posthoc.test(table)

#Menciona o glúten como a causa primária de DC

table<-with(dados_videos,table(q17,q3))
table
##    q3
## q17  1  2  3
##   1 17 30 42
##   2  3  5  2
prop.table(table)
##    q3
## q17          1          2          3
##   1 0.17171717 0.30303030 0.42424242
##   2 0.03030303 0.05050505 0.02020202
chisq.test(dados_videos$q17, dados_videos$q3)
## Warning in chisq.test(dados_videos$q17, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q17 and dados_videos$q3
## X-squared = 2.6991, df = 2, p-value = 0.2594
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona a idade que a DC pode se desenvolver

table<-with(dados_videos,table(q18,q3))
table
##    q3
## q18  1  2  3
##   1  3  7 23
##   2 17 28 21
prop.table(table)
##    q3
## q18          1          2          3
##   1 0.03030303 0.07070707 0.23232323
##   2 0.17171717 0.28282828 0.21212121
chisq.test(dados_videos$q18, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q18 and dados_videos$q3
## X-squared = 12.927, df = 2, p-value = 0.001559
chisq.posthoc.test(table)

#Menciona o risco para o desenvolvimento de outras condições crônicas de saúde

table<-with(dados_videos,table(q19,q3))
table
##    q3
## q19  1  2  3
##   1 11 17 29
##   2  9 18 15
prop.table(table)
##    q3
## q19          1          2          3
##   1 0.11111111 0.17171717 0.29292929
##   2 0.09090909 0.18181818 0.15151515
chisq.test(dados_videos$q19, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q19 and dados_videos$q3
## X-squared = 2.467, df = 2, p-value = 0.2913
chisq.posthoc.test(table)

Mencionam a inibição do crescimento em crianças

table<-with(dados_videos,table(q20,q3))
table
##    q3
## q20  1  2  3
##   1  5  9 12
##   2 15 26 32
prop.table(table)
##    q3
## q20          1          2          3
##   1 0.05050505 0.09090909 0.12121212
##   2 0.15151515 0.26262626 0.32323232
chisq.test(dados_videos$q20, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q20 and dados_videos$q3
## X-squared = 0.045081, df = 2, p-value = 0.9777
chisq.posthoc.test(table)

Menciona alterações na rotina e nas relações sociais

table<-with(dados_videos,table(q21,q3))
table
##    q3
## q21  1  2  3
##   1 11  8 17
##   2  9 27 27
prop.table(table)
##    q3
## q21          1          2          3
##   1 0.11111111 0.08080808 0.17171717
##   2 0.09090909 0.27272727 0.27272727
chisq.test(dados_videos$q21, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q21 and dados_videos$q3
## X-squared = 5.8592, df = 2, p-value = 0.05342
chisq.posthoc.test(table)

#Menciona alterações na qualidade de vida

table<-with(dados_videos,table(q22,q3))
table
##    q3
## q22  1  2  3
##   1 11  9 18
##   2  9 26 26
prop.table(table)
##    q3
## q22          1          2          3
##   1 0.11111111 0.09090909 0.18181818
##   2 0.09090909 0.26262626 0.26262626
chisq.test(dados_videos$q22, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q22 and dados_videos$q3
## X-squared = 4.8289, df = 2, p-value = 0.08942
chisq.posthoc.test(table)

Menciona comidas e bebidas que contém glúten

table<-with(dados_videos,table(q23,q3))
table
##    q3
## q23  1  2  3
##   1  4 15 22
##   2 16 20 22
prop.table(table)
##    q3
## q23          1          2          3
##   1 0.04040404 0.15151515 0.22222222
##   2 0.16161616 0.20202020 0.22222222
chisq.test(dados_videos$q23, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q23 and dados_videos$q3
## X-squared = 5.1469, df = 2, p-value = 0.07627
chisq.posthoc.test(table)

Menciona inchaço

table<-with(dados_videos,table(q24,q3))
table
##    q3
## q24  1  2  3
##   1  7 14 22
##   2 13 21 22
prop.table(table)
##    q3
## q24          1          2          3
##   1 0.07070707 0.14141414 0.22222222
##   2 0.13131313 0.21212121 0.22222222
chisq.test(dados_videos$q24, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q24 and dados_videos$q3
## X-squared = 1.5191, df = 2, p-value = 0.4679
chisq.posthoc.test(table)

Menciona diarréia crônica

table<-with(dados_videos,table(q25,q3))
table
##    q3
## q25  1  2  3
##   1 11 20 35
##   2  9 15  9
prop.table(table)
##    q3
## q25          1          2          3
##   1 0.11111111 0.20202020 0.35353535
##   2 0.09090909 0.15151515 0.09090909
chisq.test(dados_videos$q25, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q25 and dados_videos$q3
## X-squared = 5.9377, df = 2, p-value = 0.05136
chisq.posthoc.test(table)

Menciona constipação

table<-with(dados_videos,table(q26,q3))
table
##    q3
## q26  1  2  3
##   1  5  8 15
##   2 15 27 29
prop.table(table)
##    q3
## q26          1          2          3
##   1 0.05050505 0.08080808 0.15151515
##   2 0.15151515 0.27272727 0.29292929
chisq.test(dados_videos$q26, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q26 and dados_videos$q3
## X-squared = 1.346, df = 2, p-value = 0.5102
chisq.posthoc.test(table)

Menciona náuseas

table<-with(dados_videos,table(q27,q3))
table
##    q3
## q27  1  2  3
##   1  1  1  8
##   2 19 34 36
prop.table(table)
##    q3
## q27          1          2          3
##   1 0.01010101 0.01010101 0.08080808
##   2 0.19191919 0.34343434 0.36363636
chisq.test(dados_videos$q27, dados_videos$q3)
## Warning in chisq.test(dados_videos$q27, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q27 and dados_videos$q3
## X-squared = 5.7596, df = 2, p-value = 0.05614
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona dores de estômago

table<-with(dados_videos,table(q28,q3))
table
##    q3
## q28  1  2  3
##   1  8  5 18
##   2 12 30 26
prop.table(table)
##    q3
## q28          1          2          3
##   1 0.08080808 0.05050505 0.18181818
##   2 0.12121212 0.30303030 0.26262626
chisq.test(dados_videos$q28, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q28 and dados_videos$q3
## X-squared = 7.3036, df = 2, p-value = 0.02594
chisq.posthoc.test(table)

Menciona vômitos

table<-with(dados_videos,table(q29,q3))
table
##    q3
## q29  1  2  3
##   1  5  6 14
##   2 15 29 30
prop.table(table)
##    q3
## q29          1          2          3
##   1 0.05050505 0.06060606 0.14141414
##   2 0.15151515 0.29292929 0.30303030
chisq.test(dados_videos$q29, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q29 and dados_videos$q3
## X-squared = 2.225, df = 2, p-value = 0.3287
chisq.posthoc.test(table)

Menciona dermatite herpetiforme

table<-with(dados_videos,table(q30,q3))
table
##    q3
## q30  1  2  3
##   1  3  7  6
##   2 17 28 38
prop.table(table)
##    q3
## q30          1          2          3
##   1 0.03030303 0.07070707 0.06060606
##   2 0.17171717 0.28282828 0.38383838
chisq.test(dados_videos$q30, dados_videos$q3)
## Warning in chisq.test(dados_videos$q30, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q30 and dados_videos$q3
## X-squared = 0.60757, df = 2, p-value = 0.738
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona por quê os sintomas variam entre os indivíduos

table<-with(dados_videos,table(q31,q3))
table
##    q3
## q31  1  2  3
##   1  2  3  9
##   2 18 32 35
prop.table(table)
##    q3
## q31          1          2          3
##   1 0.02020202 0.03030303 0.09090909
##   2 0.18181818 0.32323232 0.35353535
chisq.test(dados_videos$q31, dados_videos$q3)
## Warning in chisq.test(dados_videos$q31, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q31 and dados_videos$q3
## X-squared = 2.6212, df = 2, p-value = 0.2697
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona os sintomas na criança

table<-with(dados_videos,table(q32,q3))
table
##    q3
## q32  1  2  3
##   1  6 11 16
##   2 14 24 28
prop.table(table)
##    q3
## q32          1          2          3
##   1 0.06060606 0.11111111 0.16161616
##   2 0.14141414 0.24242424 0.28282828
chisq.test(dados_videos$q32, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q32 and dados_videos$q3
## X-squared = 0.33896, df = 2, p-value = 0.8441
chisq.posthoc.test(table)

Menciona como é diagnosticada a DC

table<-with(dados_videos,table(q33,q3))
table
##    q3
## q33  1  2  3
##   1 10 17 29
##   2 10 18 15
prop.table(table)
##    q3
## q33         1         2         3
##   1 0.1010101 0.1717172 0.2929293
##   2 0.1010101 0.1818182 0.1515152
chisq.test(dados_videos$q33, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q33 and dados_videos$q3
## X-squared = 2.8248, df = 2, p-value = 0.2436
chisq.posthoc.test(table)

Menciona exames de sangue como forma de diagnóstico

table<-with(dados_videos,table(q34,q3))
table
##    q3
## q34  1  2  3
##   1  6 14 25
##   2 14 21 19
prop.table(table)
##    q3
## q34          1          2          3
##   1 0.06060606 0.14141414 0.25252525
##   2 0.14141414 0.21212121 0.19191919
chisq.test(dados_videos$q34, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q34 and dados_videos$q3
## X-squared = 4.6383, df = 2, p-value = 0.09836
chisq.posthoc.test(table)

Menciona a utilização da endoscopia como diagnóstico

table<-with(dados_videos,table(q35,q3))
table
##    q3
## q35  1  2  3
##   1  6 12 16
##   2 14 23 28
prop.table(table)
##    q3
## q35          1          2          3
##   1 0.06060606 0.12121212 0.16161616
##   2 0.14141414 0.23232323 0.28282828
chisq.test(dados_videos$q35, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q35 and dados_videos$q3
## X-squared = 0.24702, df = 2, p-value = 0.8838
chisq.posthoc.test(table)

Menciona a importância da testagem/rastreamento para outros membros da família

table<-with(dados_videos,table(q36,q3))
table
##    q3
## q36  1  2  3
##   1  4  3 12
##   2 16 32 32
prop.table(table)
##    q3
## q36          1          2          3
##   1 0.04040404 0.03030303 0.12121212
##   2 0.16161616 0.32323232 0.32323232
chisq.test(dados_videos$q36, dados_videos$q3)
## Warning in chisq.test(dados_videos$q36, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q36 and dados_videos$q3
## X-squared = 4.4066, df = 2, p-value = 0.1104
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona tratamento para DC

table<-with(dados_videos,table(q37,q3))
table
##    q3
## q37  1  2  3
##   1  8 22 31
##   2 12 13 13
prop.table(table)
##    q3
## q37          1          2          3
##   1 0.08080808 0.22222222 0.31313131
##   2 0.12121212 0.13131313 0.13131313
chisq.test(dados_videos$q37, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q37 and dados_videos$q3
## X-squared = 5.4274, df = 2, p-value = 0.06629
chisq.posthoc.test(table)

Menciona dieta isenta de glúten, tanto para bebidas como para comidas

table<-with(dados_videos,table(q38,q3))
table
##    q3
## q38  1  2  3
##   1  4 11 20
##   2 16 24 24
prop.table(table)
##    q3
## q38          1          2          3
##   1 0.04040404 0.11111111 0.20202020
##   2 0.16161616 0.24242424 0.24242424
chisq.test(dados_videos$q38, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q38 and dados_videos$q3
## X-squared = 4.2631, df = 2, p-value = 0.1187
chisq.posthoc.test(table)

Menciona medicações isentas de glúten

table<-with(dados_videos,table(q39,q3))
table
##    q3
## q39  1  2  3
##   1  0  4  4
##   2 20 31 40
prop.table(table)
##    q3
## q39          1          2          3
##   1 0.00000000 0.04040404 0.04040404
##   2 0.20202020 0.31313131 0.40404040
chisq.test(dados_videos$q39, dados_videos$q3)
## Warning in chisq.test(dados_videos$q39, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q39 and dados_videos$q3
## X-squared = 2.3468, df = 2, p-value = 0.3093
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona seguimento anual para avaliação e reavaliação das instruções do tratamento

table<-with(dados_videos,table(q40,q3))
table
##    q3
## q40  1  2  3
##   1  0  0  6
##   2 20 35 38
prop.table(table)
##    q3
## q40          1          2          3
##   1 0.00000000 0.00000000 0.06060606
##   2 0.20202020 0.35353535 0.38383838
chisq.test(dados_videos$q40, dados_videos$q3)
## Warning in chisq.test(dados_videos$q40, dados_videos$q3): Chi-squared
## approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q40 and dados_videos$q3
## X-squared = 7.9839, df = 2, p-value = 0.01846
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect

Menciona potenciais complicações se o plano de tratamento não for seguido

table<-with(dados_videos,table(q41,q3))
table
##    q3
## q41  1  2  3
##   1  7  8 22
##   2 13 27 22
prop.table(table)
##    q3
## q41          1          2          3
##   1 0.07070707 0.08080808 0.22222222
##   2 0.13131313 0.27272727 0.22222222
chisq.test(dados_videos$q41, dados_videos$q3)
## 
##  Pearson's Chi-squared test
## 
## data:  dados_videos$q41 and dados_videos$q3
## X-squared = 6.1963, df = 2, p-value = 0.04513
chisq.posthoc.test(table)